Imaging system for examining biological material

ABSTRACT

Improved biological material imaging systems and related methods are provided by using an imaging system for imaging biological materials, the imaging system comprising a sensor having one or more receptors, and an image transfer medium to scale the one or more receptors to an object field of view.

FIELD OF THE INVENTION

The present invention generally relates to an imaging system forexamining biological material and methods of examining biologicalmaterial.

BACKGROUND OF THE INVENTION

Microscopes give us a large image of a tiny object. Greatermagnification can be achieved if the light from an object is made topass through two lenses compared to a simple microscope with one lens. Acompound microscope has two or more converging lenses, placed in linewith one another, so that both bend and refract the light in turn. Theresult is to produce an image that is magnified more than either lenscould magnify alone. Light illuminating the object first passes througha short focal length lens or lens group, called the objective, and thentravels on some distance before being passed through a longer focallength lens or lens group, called the eyepiece. A lens group is oftensimply referred to singularly as a lens. Usually these two lenses areheld in paraxial relationship to one another, so that the axis of onelens is arranged to be in exactly the same as orientation as the axis ofthe second lens. It is the nature of the lenses, their properties, theirrelationship, and the relationship of the objective lens to the objectthat determines how a highly magnified image is produced in the eye ofthe observer.

The first lens or objective, is usually a small lens with a very smallfocal length. A specimen or object is placed in the path of a lightsource with sufficient intensity to illuminate as desired. The objectivelens is then lowered until the specimen is very close to, but not quiteat the focal point of the lens. Light leaving the specimen and passingthrough the objective lens produces a real, inverted and magnified imagebehind the lens, in the microscope at a point generally referred to asthe intermediate image plane. The second lens or eyepiece, has a longerfocal length and is placed in the microscope so that the image producedby the objective lens falls closer to the eyepiece than one focal length(that is, inside the focal point of the lens). The image from theobjective lens now becomes the object for the eyepiece lens. As thisobject is inside one focal length, the second lens bends the light insuch a way as to produce a second image that is virtual, inverted andmagnified. This is the final image seen by the eye of the observer.

Alternatively, common infinity space or infinity corrected designmicroscopes employ objective lenses with infinite conjugate propertiessuch that the light leaving the objective is not focused, but is a fluxof parallel rays which move and do not converge until after passingthrough a tube lens where the projected image is then located at thefocal point of the eyepiece for magnification and observation. Compoundmicroscopes such as described herein are commonly employed to viewbiological material.

Many microscopes, such as the compound microscope described above, aredesigned to provide images of certain quality to the human eye throughan eyepiece. Connecting a Machine Vision Sensor, such as a ChargeCoupled Device (CCD) sensor, to the microscope so that an image may beviewed on a monitor presents difficulties. This is because the imagequality provided by the sensor and viewed by a human eye decreases, ascompared to an image viewed by a human eye directly through an eyepiece.As a result, conventional optical systems for examining biologicalmaterial often require the careful attention of a technician monitoringthe process through an eyepiece. Real time images via a monitor are ofpoor quality.

While a scanning electron microscope can provide highly magnified imagesof biological material, there are several limitations associated withscanning electron microscope images. For example, it is difficult toimpossible to provide real time images of a biological material.Scanning electron microscopy is typically a destructive technique,preventing further use of the imaged sample. A scanning electronmicroscope is a large apparatus requiring dedicated facilities, and isnot portable.

SUMMARY OF THE INVENTION

The imaging system and methods of the present invention enable at leastone of finer and more precise biological material image sampling;greater working distances thereby not interfering with manipulation ofbiological material samples; closed circuit, web based, and remotemonitoring of biological material imaging; and automated process controlof biological material imaging systems and methods. For instance, usingthe biological material imaging system of the present invention enablesthe improved identification of cancerous cells in a tissue sample, theimproved identification of an unknown pathogen from a powder, theimproved classification of cells as normal or abnormal, and the improveddiagnosis of diseases/illnesses.

BRIEF SUMMARY OF THE DRAWINGS

FIG. 1 is a schematic block diagram illustrating a biological materialimaging system in accordance with an aspect of the present invention.

FIG. 2 is a diagram illustrating a k-space system design in accordancewith an aspect of the present invention.

FIG. 3 is a diagram of an exemplary system illustrating sensor receptormatching in accordance with an aspect of the present invention.

FIG. 4 is a graph illustrating sensor matching considerations inaccordance with an aspect of the present invention.

FIG. 5 is a chart illustrating exemplary performance specifications inaccordance with an aspect of the present invention.

FIG. 6 is a flow diagram illustrating a biological material imagingmethodology in accordance with an aspect of the present invention.

FIG. 7 is a flow diagram illustrating a biological material imagingmethodology in accordance with one aspect of the present invention.

FIG. 8 is a high level schematic diagram of a biological materialimaging system in accordance with one aspect of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

A novel imaging system that provides high effective resolvedmagnification and high spatial resolution among other features ofbiological material and methods are combined to provide improvedbiological material imaging systems and methods. The biological materialimaging systems and methods of the present invention enable theproduction of improved images (higher effective magnification, improvedresolution, improved depth of field, and the like) leading to theidentification of biological materials as well as the classification ofbiological materials (for example as normal or abnormal).

According to one aspect of the present invention, a k-space filter isprovided that can be configured from an image transfer medium such asoptical media that correlates image sensor receptors to an object fieldof view. A variety of illumination sources can also be employed toachieve one or more operational goals and for versatility ofapplication. The k-space design of the imaging system of the presentinvention promotes capture and analysis (e.g., automated and/or manual)of images having a high Field Of View (FOV) at substantially highEffective Resolved Magnification as compared to conventional biologicalmaterial microscopes. This can include employing a small NumericalAperture (NA) associated with lower magnification objective lenses toachieve very high Effective Resolved Magnification. As a consequence,images having a substantially large Depth Of Field (DOF) at very highEffective Resolved Magnification are also realized. The k-space designalso facilitates employment of homogeneous illumination sources that aresubstantially insensitive to changes in position, thereby improvingmethods of examining biological material.

According to another aspect of the present invention, an objective lensto biological material sample or object distance (e.g., WorkingDistance) can be maintained in operation at low and high power effectiveresolved magnification imaging, wherein typical spacing can be achievedat about 0.1 mm or more and about 20 mm or less, as opposed toconventional microscopic systems which can require significantly smaller(as small as 0.01 mm) tissue sample to objective lens distances forcomparable (e.g., similar order of magnitude) Effective ResolvedMagnification values. In another embodiment, the Working Distance isabout 0.5 mm or more and about 10 mm or less. It is to be appreciatedthat the present invention is not limited to operating at the aboveworking distances. In many instances the above working distances areemployed, however, in some instances, smaller or larger distances areemployed. It is further noted that oil immersion or other Index ofRefraction matching media or fluids for objective lenses are generallynot required (e.g., substantially no improvement to be gained) at one ormore effective image magnification levels of the present invention yet,still exceeding effective resolved magnification levels achievable inconventional biological material microscopic optical design variationsincluding systems employing “infinity-corrected” objective lenses.

The k-space design of the biological material imaging system of thepresent invention defines that a small “Blur Circle” or diffractionlimited point/spot at the object plane is determined by parameters ofthe design to match image sensor receptors or pixels with asubstantially one-to-one correspondence by “unit-mapping” of object andimage spaces for associated object and image fields. This enables theimproved performance and capabilities of the present invention. Onepossible theory of the k-space design results from the mathematicalconcept that since the Fourier Transform of both an object and an imageis formed in k-space (also called “reciprocal space”), the sensor shouldbe mapped to the object plane in k-space via optical design techniquesand component placement in accordance with the present invention. It isto be appreciated that a plurality of other transforms or models can beutilized to configure and/or select one or more components in accordancewith the present invention. For example, wavelet transforms, LaPlace(s-transforms), z-transforms as well as other transforms can besimilarly employed.

The k-space design methodology is unlike conventional biologicalmaterial optical systems designed according to geometric, paraxialray-trace and optimization theory, since the k-space optimizationfacilitates that the spectral components of the object (tissue sample)and the image are the same in k-space, and thus quantized. Therefore,there are substantially no inherent limitations imposed on a ModulationTransfer Function (MTF) describing contrast versus resolution andabsolute spatial resolution in the present invention. Quantization, forexample, in k-space yields a substantially unitary Modulation TransferFunction not realized by conventional systems. It is noted that highMTF, Spatial Resolution, and effective image magnification can beachieved with much lower magnification objective lenses with desirablelower Numerical Apertures (e.g., generally less than about 50× and at anumerical aperture generally less than about 0.7) through “unit-mapping”of projected pixels in an “Intrinsic Spatial Filter” provided by thek-space design.

If desired, “infinity-corrected” objectives can be employed withassociated optical component and illumination, as well as spectrumvarying components, polarization varying components, and/or contrast orphase varying components. These components can be included in an opticalpath-length between an objective and the image lens within an “infinityspace”. Optical system accessories and variations can thus be positionedas interchangeable modules in this geometry. The k-space design, incontrast to conventional biological material microscopic imagers thatutilize “infinity-corrected” objectives, enables the maximumoptimization of the infinity space geometry by the “unit-mapping”concept. This implies that there is generally no specific limit to thenumber of additional components that can be inserted in the “infinityspace” geometry as in conventional biological material microscopicsystems that typically specify no more than 2 additional componentswithout optical correction.

The present invention also enables a “base-module” design that can beconfigured and reconfigured in operation for a plurality of differentapplications if necessary to employ either transmissive or reflectedillumination, if desired. This includes substantially all typicalmachine vision illumination schemes (e.g., darkfield, brightfield,phase-contrast), and other microscopic transmissive techniques (Kohler,Abbe), in substantially any offset and can include Epi illumination. Thesystems of the present invention can be employed in a plurality ofopto-mechanical designs that are robust since the k-space design issubstantially not sensitive to environmental and mechanical vibrationand thus generally does not require heavy structural mechanical designand isolation from vibration associated with conventional biologicalmaterial microscopic imaging instruments. Other features can includedigital image processing, if desired, along with storage (e.g., localdatabase, image data transmissions to remote computers forstorage/analysis) and display of the images produced in accordance withthe present invention (e.g., computer display, printer, film, and otheroutput media). Remote signal processing of image data can be provided,along with communication and display of the image data via associateddata packets that are communicated over a network or other medium, forexample.

Biological material includes microorganisms (organisms too small to beobserved with the unaided eye) such as bacteria, virus, protozoans,fungi, and ciliates; cell material from organisms such cells (lysed,intracellular material, or whole cells), proteins, antibodies, lipids,and carbohydrates, tagged or untagged; and portions of organisms such asclumps of cells (tissue samples), blood, pupils, irises, finger tips,teeth, portions of the skin, hair, mucous membranes, bladder, breast,male/female reproductive system components, muscle, vascular components,central nervous system components, liver, bone, colon, pancreas, and thelike. Since the biological material imaging system of the presentinvention can employ a relatively large working distance, portions ofthe human body may be directly examined without the need for removing atissue sample.

Cells include human cells, non-human animal cells, plant cells, andsynthetic/research cells. Cells include prokaryotic and eukaryoticcells. Cells may be healthy, cancerous, mutated, damaged, or diseased.

Examples of non-human cells include anthrax, Actinomycetes spp.,Azotobacter, Bacillus anthracis, Bacillus cereus, Bacteroides species,Bordetella pertussis, Borrelia burgdorferi, Campylobacter jejuni,Chlamydia species, Clostridium species, Cyanobacteria, Deinococcusradiodurans, Escherichia coli, Enterococcus, Haemophilus influenzae,Helicobacter pylori, Klebsiella pneumoniae, Lactobacillus spp., Lawsoniaintracellularis, Legionellae, Listeria spp., Micrococcus spp.,Mycobacterium leprae, Mycobacterium tuberculosis, Myxobacteria,Neisseria gonorrheoeae, Neisseria meningitidis, Prevotella spp.,Pseudomonas spp., Salmonellae, Serratia marcescens, Shigella species,Staphylococcus aureus, Streptococci, Thiomargarita namibiensis,Treponema pallidum, Vibrio cholerae, Yersinia enterocolitica, Yersiniapestis, and the like.

Additional examples of biological material are those that cause illnesssuch as colds, infections, malaria, chlamydia, syphilis, gonorrhea,conjunctivitis, anthrax, meningitis, botulism, diarrhea, brucellosis,campylobacter, candidiasis, cholera, coccidioidomycosis, cryptococcosis,diphtheria, pneumonia, foodborne infections, glanders (burkholderiamallei), influenzae, leprosy, histoplasmosis, legionellosis,leptospirosis, listeriosis, melioidosis, nocardiosis, nontuberculosismycobacterium, peptic ulcer disease, pertussis, pneumonia, psittacosis,salmonella enteritidis, shigellosis, sporotrichosis, strep throat, toxicshock syndrome, trachoma, typhoid fever, urinary tract infections, lymedisease, and the like. As described later, the present invention furtherrelates to methods of diagnosing any of the above illnesses.

Examples of human cells include fibroblast cells, skeletal muscle cells,neutrophil white blood cells, lymphocyte white blood cells, erythroblastred blood cells, osteoblast bone cells, chondrocyte cartilage cells,basophil white blood cells, eosinophil white blood cells, adipocyte fatcells, invertebrate neurons (Helix aspera), mammalian neurons,adrenomedullary cells, melanocytes, epithelial cells, endothelial cells;tumor cells of all types (particularly melanoma, myeloid leukemia,carcinomas of the lung, breast, ovaries, colon, kidney, prostate,pancreas and testes), cardiomyocytes, endothelial cells, epithelialcells, lymphocytes (T-cell and B cell), mast cells, eosinophils,vascular intimal cells, hepatocytes, leukocytes including mononuclearleukocytes, stem cells such as haemopoetic, neural, skin, lung, kidney,liver and myocyte stem cells, osteoclasts, chondrocytes and otherconnective tissue cells, keratinocytes, melanocytes, liver cells, kidneycells, and adipocytes. Examples of research cells include transformedcells, Jurkat T cells, NIH3T3 cells, CHO, COS, etc.

A useful source of cell lines and other biological material may be foundin ATCC Cell Lines and Hybridomas, Bacteria and Bacteriophages, Yeast,Mycology and Botany, and Protists: Algae and Protozoa, and othersavailable from American Type Culture Co. (Rockville, Md.), all of whichare herein incorporated by reference. These are non-limiting examples asa litany of cells and other biological material can be listed.

The identification or classification of biological material can in someinstances lead to the diagnosis of disease. Thus, the present inventionalso provides improved systems and methods of diagnosis. For example,the present invention also provides methods for detection andcharacterization of medical pathologies such as cancer, pathologies ofmusculoskeletal systems, digestive systems, reproductive systems, andthe alimentary canal, in addition to atherosclerosis, angiogenesis,arteriosclerosis, inflamation, atherosclerotic heart disease, myocardialinfarction, trauma to arterial or veinal walls, neurodegenerativedisorders, and cardiopulmonary disorders. The present invention alsoprovides methods for detection and characterization of viral andbacterial infections. The present invention also enables assessing theeffects of various agents or physiological activities on biologicalmaterials, in both in vitro and in vivo systems. For example, thepresent invention enables assessment of the effect of a physiologicalagent, such as a drug, on a population of cells or tissue grown inculture.

Referring initially to FIG. 1, a biological material imaging system 10is illustrated in accordance with an aspect of the present invention.The imaging system 10 includes a sensor 20 having one or more receptorssuch as pixels or discrete light detectors (See e.g., illustrated belowin FIG. 3) operably associated with an image transfer medium 30. Theimage transfer medium 30 is adapted or configured to scale theproportions of the sensor 20 at an image plane established by theposition of the sensor 20 to an object field of view illustrated atreference numeral 34. A planar reference 36 of X and Y coordinates isprovided to illustrate the scaling or reduction of the apparent orvirtual size of the sensor 20 to the object field of view 34. Directionarrows 38 and 40 illustrate the direction of reduction of the apparentsize of the sensor 20 toward the object field of view 34.

The object field of view 34 established by the image transfer medium 30is related to the position of an object plane 42 that includes one ormore biological material samples (not shown). It is noted that thesensor 20 can be substantially any size, shape and/or technology (e.g.,digital sensor, analog sensor, CCD sensor, CMOS sensor, Charge InjectionDevice (CID) sensor, an array sensor, a linear scan sensor) includingone or more receptors of various sizes and shapes, the one or morereceptors being similarly sized or proportioned on a respective sensorto be responsive to light (e.g., visible, non-visible) received from theitems under examination in the object field of view 34. As light isreceived from the object field of view 34, the sensor 20 provides anoutput 44 that can be directed to a local or remote storage such as amemory (not shown) and displayed from the memory via a computer andassociated display, for example, without substantially any interveningdigital processing (e.g., straight bit map from sensor memory todisplay), if desired. It is noted that local or remote signal processingof the image data received from the sensor 20 can also occur. Forexample, the output 44 can be converted to electronic data packets andtransmitted to a remote system over a network for further analysisand/or display. Similarly, the output 44 can be stored in a localcomputer memory before being transmitted to a subsequent computingsystem for further analysis and/or display.

The scaling provided by the image transfer medium 30 is determined by anovel k-space configuration or design within the medium that promotespredetermined k-space frequencies of interest and mitigates frequenciesoutside the predetermined frequencies. This has the effect of aband-pass filter of the spatial frequencies within the image transfermedium 30 and notably defines the biological material imaging system 10in terms of resolution rather than magnification. As will be describedin more detail below, the resolution of the imaging system 10 determinedby the k-space design promotes a plurality of features in a displayed orstored image such as having high effective resolved magnification, highspatial resolution, large depth of field, larger working distances, anda unitary Modulation Transfer Function as well as other features thatfacilitate methods for examining biological material.

In order to determine the k-space frequencies, a “pitch” or spacing isdetermined between adjacent receptors on the sensor 20, the pitchrelated to the center-to-center distance of adjacent receptors and aboutthe size or diameter of a single receptor. The pitch of the sensor 20defines the Nyquist “cut-off” frequency band of the sensor. It is thisfrequency band that is promoted by the k-space design, whereas otherfrequencies are mitigated. In order to illustrate how scaling isdetermined in the imaging system 10, a small or diffraction limited spotor point 50 is illustrated at the object plane 42. The diffractionlimited point 50 represents the smallest resolvable object determined byoptical characteristics within the image transfer medium 30 and isdescribed in more detail below. A scaled receptor 54, depicted in frontof the field of view 34 for exemplary purposes, and having a sizedetermined according to the pitch of the sensor 20, is matched or scaledto be about the same size in the object field of view 34 as thediffraction limited point 50.

In other words, the size of any given receptor at the sensor 20 iseffectively reduced in size via the image transfer medium 30 to be aboutthe same size (or matched in size) to the size of the diffractionlimited point 50. This also has the effect of filling the object fieldof view 34 with substantially all of the receptors of the sensor 20, therespective receptors being suitably scaled to be similar in size to thediffraction limited point 50. As will be described in more detail below,the matching/mapping of sensor characteristics to the smallestresolvable object or point within the object field of view 34 definesthe imaging system 10 in terms of absolute spatial resolution andprofoundly enhances the operating performance of the system.

An illumination source 60 can be provided with the present invention inorder that photons can be emitted from objects in the field of view 34to enable activation of the receptors in the sensor 20. It is noted thatthe present invention can potentially be employed without anillumination source 60 if potential self-luminous objects (e.g.,fluorescent biological material sample) emit enough radiation toactivate the sensor 60. Light Emitting Diodes, however, provide aneffective illumination source 60 in accordance with the presentinvention. Substantially any illumination source 60 can be appliedincluding coherent and non-coherent sources, visible and non-visiblewavelengths. However, for non-visible wavelength sources, the sensor 20would also be suitably adapted. For example, for an infrared orultraviolet source, an infrared or ultraviolet sensor 20 would beemployed, respectively. Other illumination sources 60 can includewavelength-specific lighting, broad-band lighting, continuous lighting,strobed lighting, Kohler illumination, Abbe illumination, phase-contrastillumination, darkfield illumination, brightfield illumination, and Epiillumination. Transmissive or reflective lighting techniques can also beapplied.

Referring now to FIG. 2, a system 100 illustrates an image transfermedium 30 in accordance with an aspect of the present invention. Theimage transfer medium 30 depicted in FIG. 1 can be provided according tothe k-space design concepts described above and more particularly via ak-space filter 110 adapted, configured and/or selected to promote a bandof predetermined k-space frequencies 114 and to mitigate frequenciesoutside of this band. This is achieved by determining a pitch “P”—whichis the distance between adjacent receptors 116 in a sensor (not shown)and sizing optical media within the filter 110 such that the pitch “P”of the receptors 116 is matched in size with a diffraction-limited spot120. The diffraction-limited spot 120 can be determined from the opticalcharacteristics of the media in the filter 110. For example, theNumerical Aperture of an optical medium such as a lens defines thesmallest object or spot that can be resolved by the lens. The filter 110performs a k-space transformation such that the size of the pitch iseffectively matched, “unit-mapped”, projected, correlated, and/orreduced to the size or scale of the diffraction limited spot 120.

It is to be appreciated that a plurality of novel optical configurationscan be provided to achieve the k-space filter 110. One suchconfiguration can be provided by an aspherical lens 124 adapted such toperform the k-space transformation and reduction from sensor space toobject space. Yet another configuration can be provided by a multiplelens arrangement 128, wherein the lens combination is selected toprovide the filtering and scaling. Still yet another configuration canemploy a fiber optic taper 132 or image conduit, wherein multipleoptical fibers or array of fibers are configured in a funnel-shape toperform the mapping of the sensor to the object field of view. It isnoted that the fiber optic taper 132 is generally in physical contactbetween the sensor and the object under examination (e.g., contact withmicroscope slide). Another possible k-space filter 110 arrangementemploys a holographic or other diffractive or phase optical element 136,wherein a substantially flat optical surface is configured via ahologram or other diffractive or phase structure (e.g.,computer-generated, optically generated, and/or other method) to providethe mapping in accordance with the present invention.

The k-space optical design as enabled by the k-space filter 110 is basedupon the “effective projected pixel-pitch” of the sensor, which is afigure derived from following (“projecting”) the physical size of thesensor array elements back through the optical system to the objectplane. In this manner, conjugate planes and optical transform spaces arematched to the Nyquist cut-off of the effective receptor or pixel size.This maximizes the effective image magnification and the Field Of Viewas well as the Depth Of Field and the Absolute Spatial Resolution. Thus,a novel application of optical theory is provided that does not rely onconventional geometric optical design parameters of paraxial ray-tracingwhich govern conventional optics and imaging combinations. This canfurther be described in the following manner.

A Fourier transform of an object and an image is formed (by an opticalsystem) in k-space (also referred to as “reciprocal-space”). It is thistransform that is operated on for image optimization by the k-spacedesign of the biological material imaging system of the presentinvention. For example, the optical media employed in the presentinvention can be designed with standard, relatively non-expensive“off-the-shelf” components having a configuration which defines that theobject and image space are “unit-mapped” or “unit-matched” forsubstantially all image and object fields. A small Blur-circle ordiffraction-limited spot 120 at the object plane is defined by thedesign to match the pixels in the image plane (e.g., at the image sensorof choice) with substantially one-to-one correspondence and thus theFourier transforms of pixelated arrays can be matched. This impliesthat, optically by design, the Blur-circle is scaled to be about thesame size as the receptor or pixel pitch. The biological materialimaging system of the present invention is defined such that itconstructs an Intrinsic Spatial Filter such as the k-space filter 110.Such a design definition and implementation enables the spectralcomponents of both the object and the image in k-space to be about thesame or quantized. This also defines that the Modulation TransferFunction (MTF) (the comparison of contrast to spatial resolution) of thesensor is matched to the MTF of the object Plane.

Turning now to FIG. 3, a multiple lens system 200 illustrates anexemplary unit-mapping design in accordance with an aspect of thepresent invention. The system 200 includes an M by N array 210 of sensorpixels (e.g., 640×480, 512×512, 1024×1280, etc.), having M rows and Ncolumns, M and N being integers respectively. Although a rectangulararray 210 having square pixels is depicted, it is to be appreciated asnoted above, the array 210 can be substantially any shape such ascircular, elliptical, hexagonal, rectangular, etc. wherein respectivepixels within the array 210 can also be substantially any shape or size,the pixels in any given array 210 being similarly sized and spaced.Unit-mapping can be determined for a plurality of sensors and lenscombinations. For example, a substantially-wide diameter achromaticobjective lens 214 (e.g., about 10 millimeters or more to about 100millimeters or less in diameter) can be selected to preserve k-spacefrequencies of interest and having a Numerical Aperture capable ofresolving diffraction-limited spots 218 of about 1 micron, for example,and having a focal length “D1” of about 1 centimeter. It is noted thatthe dimensions selected for the system 200 are provided for exemplarypurposes to facilitate understanding of the concepts described above.Thus, for example, if an objective lens 214 is selected that is capableof resolving diffraction limited spots 218 having other dimensions(e.g., about 0.2, about 0.3, about 0.4, about 0.6 microns, etc.), then adifferent lens, sensor and/or lens/sensor combination is selected toprovide the scaling and/or unit-mapping in accordance with the presentinvention.

In order to provide unit-mapping according to this example, and assumingfor purposes of illustration that the sensor array 210 provides a pixelpitch “P” of about 10 microns, a relationship is to be determinedbetween an achromatic transfer lens 230 and the objective lens 214 suchthat a reduction is achieved from sensor space defined at the array 210to object space defined at an object plane 234 and thus, scalingrespective pixels from the array 210 to about the size of thediffraction limited spot 218. It is noted that substantially all of thepixels are projected into an object field of view depicted at referencenumeral 238 and defined by the objective lens 214, wherein respectivepixels are sized to about the dimensions of the diffraction limited spot218. The reduction in size of the array 210 and associated pixels can beachieved by selecting the transfer lens to have a focal length “D2”(from the array 210 to the transfer lens 230) of about 10 centimeters inthis example. In this manner, the pixels in the array 210 areeffectively reduced in size to about 1 micron per pixel, thus matchingthe size of the diffraction limited spot 218 and filling the objectfield of view 238 with a “virtually-reduced” array of pixels 210.

As illustrated in FIG. 3, k-space is defined as the region between theobjective lens 214 and the transfer lens 230. It is to be appreciatedthat substantially any optical media, lens type and/or lens combinationthat reduces, maps and/or projects the sensor array 210 to the objectfield of view 238 in accordance with unit or k-space mapping as has beenpreviously described is within the scope of the present invention. Toillustrate the novelty of the exemplary lens/sensor combination depictedin FIG. 3, it is noted that conventional objective lenses for examiningbiological material, sized according to conventional geometric paraxialray techniques, are generally sized according to the magnification,Numeric Aperture, focal length and other parameters provided by theobjective. Thus, the objective lens would be sized with a greater focallength than subsequent lenses that approach or are closer to the sensor(or eyepiece in conventional microscope) in order to providemagnification of small objects. This can result in magnification of thesmall objects at the object plane being projected as a magnified imageof the objects across “portions” of the sensor and results in knowndetail blur (e.g., Rayleigh diffraction and other limitations in theoptics), empty magnification problems, and Nyquist aliasing among otherproblems at the sensor. The k-space design of the biological materialimaging system of the present invention operates as an alternative togeometric paraxial ray design principles. As illustrated in FIG. 3, theobjective lens 214 and the transfer lens 230 operate to provide areduction in size of the sensor array 210 to the object field of view238 as demonstrated by the relationship of the lenses.

Referring now to FIG. 4, a graph 300 illustrates mapping characteristicsand comparison between projected pixel size on the X axis anddiffraction-limited spot resolution size “R” on the Y axis. At the apex310 of the graph 300, a unit mapping between projected pixel size anddiffraction-limited spot size occurs which is the optimum relationshipin accordance with the biological material imaging system of the presentinvention. It is noted that the objective lens 214 depicted in FIG. 3need generally not be selected such that the diffraction-limited size“R” of the smallest resolvable objects is smaller than a projected pixelsize. If so, “economic waste” can occur wherein more precise informationis lost (e.g., selecting an object lens more expensive than required).This is illustrated to the right of a dividing line 320 at reference 324depicting a projected pixel larger that two smaller diffraction spots.If an objective is selected with diffraction-limited performance largerthan the projected pixel size, blurring and empty magnification canoccur. This is illustrated to the left of line 320 at reference numeral330, wherein a projected pixel 334 is smaller than a diffraction-limitedobject 338. It is to be appreciated, however, that even if substantiallyone-to-one correspondence is not achieved between projected pixel sizeand the diffraction-limited spot, a system can be configured with lessthan optimum matching (e.g., about 0.1% or more, about 1% or more, about2% or more, about 5% or more, about 20% or more, about 95% or more downfrom the apex 330 on the graph 300 to the left or right of the line 320)and still provide suitable performance. Thus, less than optimal matchingis intended to fall within the spirit and the scope of presentinvention. It is further noted that the diameter of the lenses in thesystem as illustrated in FIG. 3, for example, can be sized such thatwhen a Fourier Transform is performed from object space to sensor space,spatial frequencies of interest that are in the band pass regiondescribed above (e.g., frequencies utilized to define the size and shapeof a pixel) are substantially not attenuated. This generally impliesthat larger diameter lenses (e.g., about 10 to about 100 millimeters)are typically selected to mitigate attenuation of the spatialfrequencies of interest.

FIG. 5 illustrates a chart 400 of exemplary and typical performanceparameters that can be achieved via the k-space design of the biologicalmaterial imaging system of the present invention employing standard,low-cost, and commercially available components such as dry objectivelenses, a 1024×1280 sensor, LED illumination source wavelengths selectedat about twice the wavelength of the desired resolution (e.g., for 200nanometer resolution, 400 nanometer light source selected), and astraight bit map from sensor to image display without intervening signalprocessing. Custom components can be alternatively fabricated. As can beobserved, effective resolved magnifications of about 5000 times can beachieved at an absolute spatial resolution of about 200 nanometers in atypical non-optimized system. As used herein, the term “EffectiveResolved Magnification” is utilized to objectively compare the relativeapparent image size and Absolute Spatial Resolution of the biologicalmaterial imaging system of the present invention with conventionalbiological material microscopic imaging systems.

In one embodiment, the images produced in accordance with the presentinvention have a depth of field of about 1 micron or more and about 50microns or less at an Effective Resolved Magnification of about 750times or more and about 5000 times or less. In another embodiment, theimages produced in accordance with the present invention have a depth offield of about 10 microns or more and about 40 microns or less at anEffective Resolved Magnification of about 750 times or more and about2500 times or less. In yet another embodiment, the images produced inaccordance with the present invention have a depth of field of about 5microns or more and about 50 microns or less at an Effective ResolvedMagnification of about 400 times or more and about 2000 times or less.

In one embodiment, the images produced in accordance with the presentinvention have an effective resolved magnification of about 2500 timesor more and about 5000 times or less while providing a spatial field ofview of about 0.250 millimeters or less. In another embodiment, theimages produced in accordance with the present invention have aneffective resolved magnification of about 500 times or more and about2500 times or less while providing a spatial field of view of about 0.2millimeters or less.

FIG. 6 illustrates a methodology 500 to facilitate biological materialimaging performance in accordance with the present invention. While, forpurposes of simplicity of explanation, the methodology is shown anddescribed as a series of acts, it is to be understood and appreciatedthat the present invention is not limited by the order of acts, as someacts may, in accordance with the present invention, occur in differentorders and/or concurrently with other acts from that shown and describedherein. For example, those skilled in the art will understand andappreciate that a methodology could alternatively be represented as aseries of interrelated states or events, such as in a state diagram.Moreover, not all illustrated acts may be required to implement amethodology in accordance with the present invention.

Proceeding to 510, lenses are selected having diffraction-limitedcharacteristics at about the same size of a pixel in order to provideunit-mapping and optimization of the k-space design. At 514, lenscharacteristics are also selected to mitigate reduction of spatialfrequencies within k-space. As described above, this generally impliesthat larger diameter optics are selected in order to mitigateattenuation of desired k-space frequencies of interest. At 518, a lensconfiguration is selected such that pixels, having a pitch “P”, at theimage plane defined by the position of a sensor are scaled according tothe pitch to an object field of view at about the size of adiffraction-limited spot (e.g., unit-mapped) within the object field ofview. At 522, an image is generated by outputting data from a sensor forreal time monitoring and storing the data in memory for direct displayto a computer display and/or subsequent local or remote image processingand/or analysis within the memory.

FIG. 7 illustrates another methodology that can be employed to design abiological material imaging system in accordance with an aspect of thepresent invention. The methodology begins at 600 in which an appropriatesensor array is chosen for the biological material imaging system. Thesensor array includes of a matrix of receptor pixels having a knownpitch size, usually defined by the manufacturer. The sensor can besubstantially any shape (e.g., rectangular, circular, square,triangular, and so forth). By way of illustration, assume that a simplesensor of 640×480 pixels having a pitch size of 10 μm is chosen. It isto be understood and appreciated that a biological material imagingsystem can be designed for any type and/or size of sensor array inaccordance with the present invention.

Next at 610, an image resolution is defined. The image resolutioncorresponds to the smallest desired resolvable spot size at the imageplane. The image resolution can be defined based on the specificapplication(s) for which the biological material imaging system is beingdesigned, such as any resolution that is greater than or equal to asmallest diffraction limited size. Thus, it is to be appreciated thatresolution becomes a selectable design parameter that can be tailored toprovide desired image resolution for virtually any type of application.In contrast, most conventional biological material imaging systems tendto limit resolution according to Rayleigh diffraction, which providesthat intrinsic spatial resolution of the lenses cannot exceed limits ofdiffraction for a given wavelength.

After selecting a desired resolution (610), an appropriate amount ofmagnification is determined at 620 to achieve such resolution. Forexample, the magnification is functionally related to the pixel pitch ofthe sensor array and the smallest resolvable spot size. Themagnification (M) can be expressed as follows:M=x/y  Eq. 1

-   -   where:        -   x is the pixel pitch of the sensor array; and        -   y is the desired image resolution (minimum spot size).            So, for the above example where the pixel pitch is 10 μm and            assuming a desired image resolution of 1 μm, Eq. 1 provides            a biological material imaging system of power ten. That is,            the lens system is configured to back-project each 10 μm            pixel to the object plane and reduce respective pixels to            the resolvable spot size of 1 micron.

The methodology of FIG. 7 also includes a determination of a NumericalAperture at 630. The Numerical Aperture (NA) is determined according towell established diffraction rules that relate NA of the objective lensto the minimum resolvable spot size determined at 610 for the biologicalmaterial imaging system. By way of example, the calculation of NA can bebased on the following equation: $\begin{matrix}{{NA} = \frac{0.5 \times \lambda}{y}} & {{Eq}.\quad 2}\end{matrix}$

-   -   where:        -   λ is the wavelength of light being used in the optical            system; and        -   y is the minimum spot size (e.g., determined at 610).

Continuing with the example in which the biological material imagingsystem has a resolved spot size of y=1 micron, and assuming a wavelengthof about 500 nm (e.g., green light), a NA=0.25 satisfies Eq. 2. It isnoted that relatively inexpensive commercially available objectives ofpower 10 provide numerical apertures of 0.25.

It is to be understood and appreciated that the relationship between NA,wavelength and resolution represented by Eq. 2 can be expressed indifferent ways according to various factors that account for thebehavior of objectives and condensers. Thus, the determination at 630,in accordance with an aspect of the present invention, is not limited toany particular equation but instead simply obeys known general physicallaws in which NA is functionally related to the wavelength andresolution. After the lens parameters are designed according to theselected sensor (600), the corresponding optical components can bearranged to provide a biological material imaging system (640) inaccordance with an aspect of the present invention.

Assume, for purposes of illustration, that the example biologicalmaterial imaging system created according to the methodology of FIG. 7is to be used for microscopy. By way of comparison, in classicalmicroscopy, in order to image structures of a size approaching 1 micron(and below), magnifications of many hundreds usually are required. Thebasic reason for this is that such optics conventionally are designedfor the situation when the sensor of choice is the human eye. Incontrast, the methodology of FIG. 7 designs the biological materialimaging system around the sensor, which affords significant performanceincreases at reduced cost.

In the k-space design methodology, according to an aspect of the presentinvention, the biological material imaging system is designed around adiscrete sensor that has known fixed dimensions. As a result, themethodology provides a far more straight-forward optical system designapproach to “back-project” the sensor size onto the object plane andcalculate a magnification factor. A second part of the methodology helpsensure that the optics that provide the magnification have a sufficientNA to optically resolve a spot of the same dimensions as theback-projected pixel. Advantageously, a biological material imagingsystem designed in accordance with an aspect of the present inventioncan utilize custom and/or off-the-shelf components. Thus, for thisexample, inexpensive optics can be employed in accordance with an aspectof the present invention to obtain excellent results, but well-correctedmicroscope optics are relatively inexpensive. If custom-designed opticsare utilized, in accordance with an aspect of the present invention,then the range of permissible magnifications and numerical aperturesbecomes immense, and some performance gains can be realized over the useof off-the-shelf optical components.

In accordance with the concepts described above in relation to FIGS.1-7, a plurality of related biological material imaging applications andmethods can be enabled and enhanced by the present invention. Forexample, these applications can include but are not limited to imaging,control, inspection, microscopy and/or other analysis.

The biological material imaging system of the present invention enablescomputer driven control or automated process control to obtain data frombiological material samples. In this connection, a computer orprocessor, coupled with the biological material imaging system, containsor is coupled to a memory or data base containing images of biologicalmaterial, such as diseased cells of various types. In this context,automatic designation of normal and abnormal biological material may bemade. The biological material imaging system secures images from a givenbiological material sample, and the images are compared with images inthe memory, such as images of diseased cells in the memory. In onesense, the computer/processor performs a comparison analysis ofcollected image data and stored image data, and based on the results ofthe analysis, formulates a determination of the identity of a givenbiological material; of the classification of a given biologicalmaterial (normal/abnormal, cancerous/noncancerous, benign/malignant,infected/not infected, and the like); and/or of a condition (diagnosis).

If the computer/processor determines that a sufficient degree ofsimilarity is present between particular images from a biologicalmaterial sample and saved images (such as of diseased cells or of thesame biological material), then the image is saved and data associatedwith the image may be generated. If the computer/processor determinesthat a sufficient degree of similarity is not present between particularimage of a biological material sample and saved images of diseasedcells/particular biological material, then the biological materialsample is repositioned and additional images are compared with images inthe memory. It is to be appreciated that statistical methods can beapplied by the computer/processor to assist in the determination that asufficient degree of similarity is present between particular imagesfrom a biological material sample and saved images of biologicalmaterial. Any suitable correlation means, memory, operating system,analytical component, and software/hardware may be employed by thecomputer/processor.

Referring to FIG. 8, an exemplary embodiment of an automated biologicalmaterial imaging system 700 in accordance with one aspect of the presentinvention enabling computer driven control or automated process controlto obtain data from biological material samples is shown. The imagingsystems 702 described in connection with FIGS. 1-7 may be employed tocapture an image of a biological material 704. The imaging system 702 iscoupled to a processor 706 or computer that reads the image generated bythe imaging system 702 and compares the image to a variety of images inthe data store 708.

The processor 706 contains an analysis component to make the comparison.Some of the many algorithms used in image processing include convolution(on which many others are based), FFT, DCT, thinning (orskeletonisation), edge detection and contrast enhancement. These areusually implemented in software but may also use special purposehardware for speed. FFT (fast Fourier transform) is an algorithm forcomputing the Fourier transform of a set of discrete data values. Givena finite set of data points, for example, a periodic sampling taken froma real-world signal, the FFT expresses the data in terms of itscomponent frequencies. It also addresses the essentially identicalinverse concerns of reconstructing a signal from the frequency data. DCT(discrete cosine transform) is technique for expressing a waveform as aweighted sum of cosines. There are a few programming languages designedfor image processing, e.g. CELIP (cellular language for imageprocessing) and VPL (visual programming language).

The data store 708 contains one or more sets of predetermined images.The images may include normal images of various biological materialsand/or abnormal images of various biological materials (diseased,mutated, physically disrupted, and the like). The images stored in thedata store 708 provide a basis to determine whether or not a givencaptured image is similar or not similar (or the degree of similarity)to the stored images. In one embodiment, the automated biologicalmaterial imaging system 700 can be employed to determine if a biologicalmaterial sample is normal or abnormal. For example, the automatedbiological material imaging system 700 can identify the presence ofdiseased cells, such as cancerous cells, in a biological materialsample, thereby facilitating diagnosis of a given disease or condition.In another embodiment, the automated biological material imaging system700 can diagnose any of the illnesses/diseases listed above by eitheridentifying the presence of an illness causing biological material (suchas an illness causing bacteria described above) or determining that agiven biological material is infected with an illness causing entitysuch as a bacteria or determining that a given biological material isabnormal (cancerous).

In yet another embodiment, the automated biological material imagingsystem 700 can be employed to determine the identity of a biologicalmaterial of unknown origin. For example, the automated biologicalmaterial imaging system 700 can identify a white powder as containinganthrax. The automated biological material imaging system 700 can alsofacilitate processing biological material, such as performing whiteblood cell or red blood cell counts on samples of blood.

The computer/processor may be coupled to a controller which controls aservo motor or other means of moving the biological material samplewithin the object plane so that remote/hands free imaging isfacilitated. That is, motors, adjusters, or other mechanical means canbe employed to move the biological material sample slide within theobject field of view.

Moreover, since the images of the biological material examinationprocess are optimized for viewing from a computer screen, television, orclosed circuit monitor, remote and web based viewing and control may beimplemented. Real time imaging facilitates at least one of rapiddiagnosis, data collection/generation, and the like.

In another embodiment, the biological material imaging system isdirected to a portion of a human (such as lesion on an arm, haze on thecornea, and the like) and images formed. The images are sent to acomputer/processor, which is instructed to identify the possiblepresence of a particular type of diseased cell (an image of which isstored in memory). Once a diseased cell is identified, thecomputer/processor instructs the system to remove/destroy the diseasedcell, for example, using a laser, liquid nitrogen, cutting instrument,and the like.

While the invention has been explained in relation to certainembodiments, it is to be understood that various modifications thereofwill become apparent to those skilled in the art upon reading thespecification. Therefore, it is to be understood that the inventiondisclosed herein is intended to cover such modifications as fall withinthe scope of the appended claims.

1-18. (canceled)
 19. A biological material imaging system, comprising:an imaging system for imaging a portion of a biological material sample,the imaging system comprising: a sensor having one or more receptors,the one or more receptors having a receptor size parameter; and an imagetransfer medium having a diffraction limited spot size in an objectfield of view, the image transfer medium operative to scale the receptorsize parameter in the object field of view to about the diffractionlimited spot size in the object field of view; a memory comprisingstored biological material image data; and a processor for comparingimage data generated by the imaging system to stored biological materialimage data, the processor coupled to the memory.
 20. The biologicalmaterial imaging system of claim 19, the image transfer medium providinga k-space filter that correlates a pitch associated with the one or morereceptors to a diffraction-limited spot within the object field of view,the pitch being unit-mapped to about the size of the diffraction-limitedspot within the object field of view.
 21. The biological materialimaging system of claim 19, the image data generated by the imagingsystem being sent via data packets to a remotely located processor. 22.The biological material imaging system of claim 19, the image transfermedium comprising a multiple lens configuration, the multiple lensconfiguration comprising a first lens positioned toward the object fieldof view and a second lens positioned toward the sensor, the first lenssized to have a focal length smaller than the second lens to provide anapparent reduction of the one or more receptors within the object fieldof view.
 23. The biological material imaging system of claim 19comprising a cancer detection system, the processor compares the imagedata generated by the imaging system to stored biological material imagedata and determines if biological material sample is cancerous ornoncancerous.
 24. The biological material imaging system of claim 19,the biological material sample has an unknown identity, and theprocessor determines the identity of the biological material sample. 25.The biological material imaging system of claim 19, the biologicalmaterial sample comprising anthrax.
 26. The biological material imagingsystem of claim 19, the processor determines the presence of diseasedcells by comparing image data generated by the imaging system to storedbiological material image data.
 27. A biological material imagingsystem, comprising: an imaging system for imaging a portion of abiological material sample, the imaging system comprising: a sensorcomprising pixels, the pixels having a pixel size parameter; and animage transfer medium having a diffraction limited spot size in anobject field of view, the image transfer medium operative to scale thepixel size parameter in the object field of view to about thediffraction limited spot size in the object field of view, the imagetransfer medium comprising a multiple lens configuration, the multiplelens configuration comprising a first lens positioned toward the objectfield of view and a second lens positioned toward the sensor, the firstlens sized to have a focal length smaller than the second lens toprovide an apparent reduction of the one or more receptors within theobject field of view; a memory comprising stored biological materialimage data; and a processor for comparing image data generated by theimaging system to stored biological material image data, the processorcoupled to the memory.
 28. The biological material imaging system ofclaim 27 having a substantially unitary Modulation Transfer Function.29. The biological material imaging system of claim 27, the biologicalmaterial sample comprising at least one selected from the groupconsisting of human cells, non-human animal cells, cancerous cells,plant cells, and synthetic cells.
 30. A method of processing abiological material sample, comprising: imaging at least a portion of abiological material sample using an imaging system, the imaging systemcomprising a sensor comprising receptors having a receptor sizeparameter and an image transfer medium having a diffraction limited spotsize in an object field of view, the image transfer medium operative toscale the receptor size parameter in the object field of view to aboutthe diffraction limited spot size in the object field of view; andcomparing image data of the biological material sample to storedbiological material image data.
 31. The method of claim 30 the storedbiological material image data comprises cancerous cell data, and themethod determines if the biological material sample is cancerous. 32.The method of claim 30, the biological material sample being of unknownidentity, the method determines an identity of the biological materialsample.
 33. The method of claim 30, the stored biological material imagedata comprises diseased cell data, and the method determines if thebiological material sample has a disease.
 34. The method of claim 30,the biological material sample comprising blood and the storedbiological material image data comprises blood cell data.
 35. The methodof claim 30, the biological material sample comprising at least one ofhuman cells and bacteria.
 36. The method of claim 30, the biologicalmaterial sample comprising at least one selected from the groupconsisting of human cells, non-human animal cells, plant cells, andsynthetic cells.
 37. The method of claim 30, wherein imaging thebiological material sample is performed remotely from comparing imagedata of the biological material sample to the stored biological materialimage data.
 38. The method of claim 30, the image transfer mediumcomprising a multiple lens configuration, the multiple lensconfiguration comprising a first lens positioned toward the object fieldof view and a second lens positioned toward the sensor, the first lenssized to have a focal length smaller than the second lens to provide anapparent reduction of the receptors within the object field of view.